Navegando por Palavras-chave "Computed tomography (CT)"

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    How useful is preoperative imaging for tumor, node, metastasis (TNM) staging of gastric cancer? A meta-analysis
    (Springer, 2012-09-01) Seevaratnam, Rajini; Cardoso, Roberta; Mcgregor, Caitlin; Lourenço, Laércio Gomes [UNIFESP]; Mahar, Alyson; Sutradhar, Rinku; Law, Calvin; Paszat, Lawrence; Coburn, Natalie; Sunnybrook Hlth Sci Ctr; Universidade Federal de São Paulo (UNIFESP); Queens Univ; Univ Toronto; Inst Clin Evaluat Sci
    Background Surgery is the fundamental curative option for gastric cancer patients. Imaging scans are routinely prescribed in an attempt to stage the disease prior to surgery. Consequently, the correlation between radiology exams and pathology is crucial for appropriate treatment planning.Methods Systematic searches were conducted using Medline, Embase, and the Cochrane Central Register of Controlled Trials from January 1, 1998 to December 1, 2009. We calculated the accuracy, overstaging rate, understaging rate, Kappa statistic, sensitivity, and specificity for abdominal ultrasound (AUS), computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) with respect to the gold standard (pathology). We also compared the performance of CT by detector number and image type. A meta-analysis was performed.Results for pre-operative T staging MRI scans had better performance accuracy than CT and AUS; CT scanners using >= 4 detectors and multi-planar reformatted (MPR) images had higher staging performances than scanners with <4 detectors and axial images only. for pre-operative N staging PET had the lowest sensitivity, but the highest specificity among modalities; CT performance did not significantly differ by detector number or addition of MPR images. for pre-operative M staging performance did not significantly differ by modality, detector number, or MPR images.Conclusions the agreement between pre-operative TNM staging by imaging scans and post-operative staging by pathology is not perfect and may affect treatment decisions. Operator dependence and heterogeneity of data may account for the variations in staging performance. Physicians should consider this discrepancy when creating their treatment plans.